You and your collaborators have been pioneering a novel method to track neurogenesis—the growth of new neurons—in the living human brain. Your approach uses Magnetic Resonance Spectroscropy (MRS) to look for telltale signals given off by neural stem cells. What is the key significance of this work, in your view?

Mirjana Maletic-Savatic: The development of the methodology to detect neural stem cells in the human brain is the key significance of our work. People have tried various approaches over the past 20 years to capitalize on Magnetic Resonance Spectroscopy (MRS) as a noninvasive, functionally meaningful imaging method. Unlike MRI scans, which provide a photograph of the brain, MRS tells us about the processes that are going on in the cells far before structural changes are evident. MRS looks at small molecules—metabolites—present in cells and tissues, including amino acids, sugars, fatty acids, lipids, neurotransmitters, etc. Molecules that are enriched in neural stem cells are one example.

With a few exceptions, these molecules are present in low quantities in the brain, which makes them very difficult to study. We have been trying to develop novel mathematical approaches to isolate spectroscopic signals from molecules with very small intensities—to identify telltale signal patterns that could serve as biomarkers for these molecules. But progress has been limited by the difficulties in acquiring quantifiable data. Petar M. Djurić, Ph.D., our Stony Brook collaborator who is an expert in engineering and applied mathematics, has focused on working out how to do this in the living human brain.

First, we had to find a biomarker for the cells and confirm that the biomarker was enriched in only those cells. Then we looked for the same signal in the animal brain, in the area where neural stem cells are found. In doing so, it became clear that we needed better signal-processing methods to isolate this signal, which was very small. Traditional techniques did not work.

Explain the importance of finding biomarkers and how this methodology might help us understand the roles of other small molecules in the brain.

MMS: When we talk about biomarkers, we’re referring to telltale biological signals that indicate the presence of a particular molecule associated with a disease or condition. (Elevated blood sugar levels, for example, is a biomarker for diabetes.) In general, the identification of reliable biomarkers would enable better diagnosis, prognostic prediction, and treatment evaluation for a range of medical conditions. Currently, we are limited by the tools that we have. To detect certain conditions and disease, we can perform behavioral assessments, neurological exams, and other tests, but what we really need in so many aspects of clinical neurology are reliable biomarkers.

The hope is that we can use the methodology we have developed to detect biomarkers not only from neural stem cells, but also from any other small molecules that are present in low concentrations in the brain—molecules that we know are there and we know are performing important roles in cellular physiology. But we have not been able to figure out how to pull out the relevant signals from all the noise using traditional methods.

What is “metabolomics”? Why study small molecules?

MMS: In the last decade or so, we have witnessed the emergence of a novel, so-called “systems-biology” approach to studying complex biological processes. This approach is expected to ultimately contribute to personalized medical care. Genomics was first of the “-omics,” or systems-biology, sciences, and it has driven enormous breakthroughs in medicine by analyzing huge sets of genes at the same time. Other “-omics” applications have been developed since, including the new field called metabolomics.

Metabolomics looks at very small molecules that are vital to cell functioning and are at the intersection of gene-environment interactions. It’s evident that environmental events can influence these molecules, and the effects can be transferred to the genome and back to the molecules. By studying them, we may find features of diseases that we have not been able to test directly through genetic or other types of analyses. This is critical for the development of noninvasive diagnostic or prognostic tests for many human diseases. Metabolomics has already shown promise in cancer research.

You are currently using these algorithms to track neurogenesis in premature infants. Where are you with that work?

MMS: As a child neurologist, my interest is in early brain development. The Dana grant was awarded to test whether an increased risk of developing mental retardation after premature birth is related to the possible lack of neural stem cells in the brain. We would like to develop routine tests that could provide useful prognostic information about the future cognitive development of these children.

It’s very clear that early brain-developmental disorders are a huge burden on societies, families, and individuals. Many studies have shown that the earlier we start to intervene therapeutically, the better babies do because of the extreme plasticity of the brain during the first two years of life. The goal is to try to help babies at risk as soon as possible in the best possible way so that we’re offering every opportunity for the brain to grow and become as close to healthy and normal as possible.

Our prospective study is underway. We hope to scan 10 to 15 babies within a week of their birth and again when they are 18 months old, with complementary neuropsychological and neurological evaluations. The goal is to correlate the degree of neurogenesis at birth and 18 months with these other measures, and then compare those data to healthy babies and to healthy 18-month olds.

The original paper reporting your method for tracking neural stem cells in the human brain was published in Science in 2007. How have the findings been received in the scientific community?

MMS: The approach we published in 2007 has been met with diametrically opposite views. People either love it or hate it. Some reviewers have raised questions about the methodology and the validity of the algorithms when applied to different settings.

During the last two years, our lab has been working on validating the method in collaboration with Dr. Djurić. We’ve done many different biological validations to confirm that the algorithm is indeed isolating and detecting the weak signals that the neural stem cells are giving off. We have run thousands of tests to detect the signals in simulated and semi-simulated conditions. And we have analyzed spectroscopy data from about 100 volunteers in order to figure out when this method is valid. These results are being submitted to a high-profile journal for publication.

Further, we are working on identifying the molecular structure of the biomarker that is enriched in neural stem cells. It seems that it is a complex lipid with some peptide structure associated with it. We have much more to do to be sure we have the right molecule, and we are performing those studies.

How are the findings being used by others who are interested in the potential role of neurogenesis in diseases?

MMS: Neurogenesis has been widely investigated over the past 20 years and appears to be important for learning and memory and for mood disorders such as depression. Antidepressants, for example, seem to directly affect neurogenesis. All of the neurogenesis studies to date have been done in animals, and there are a lot of unanswered questions. More animal studies are needed, but we also need human data before we can make any real conclusions.

Our collaborative efforts include work with Columbia University looking at neurogenesis for depression, a study that is near completion; with Harvard/Massachusetts General Hospital for schizophrenia and cognition; with New York University for investigations of Alzheimer’s and dementia; and with the University of Norway in Oslo for epilepsy. We are studying both psychiatric and neurologic disorders associated with cognitive dysfunction in adults and in children. In each case, we are examining what is happening to the neural precursor cells as these diseases develop or progress.

What would you like to see happen next to move this work forward?

MMS: I hope that our paper on the validation of the methodology used to detect low signals from MRS will be accepted by a wide scientific community and that our algorithms will be available to those scientists who are interested in using them.

Right now this is the only direct methodology to look at the roles that neural stem cells play in the human brain. My hope is that it will be validated by others and that it will help in clinical medicine to test whether neurogenesis is a factor in the development of certain disorders, or is a therapeutic possibility for other diseases. If we know that certain drugs or modalities, such as physical activity, enriched environments, and so on can increase neurogenesis, then we can develop specific therapeutic interventions to increase it. However, we need to test this in people and not only in animal models. If we had a methodology to assess neurogenesis in humans who suffer from the disorders that seem to be associated with it—akin to say, a blood-sugar test for diabetes—that would really be a major achievement.